Factor Investing in Corporate Bond Markets: Enhancing Efficacy Through Diversification and Purification!

T. Heckel, Zine Amghar, Isaac Haik, Olivier Laplénie, Raul Leote de Carvalho
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引用次数: 6

Abstract

We show that factors from value, quality, low-risk, and momentum styles play an important role in explaining the cross-section of corporate bond expected returns for the US and Euro Investment Grade and US BB-B Nonfinancial High Yield universes. We demonstrate the importance of purifying factor data by neutralizing a number of risk biases that are present in the factors: controlling for sectors, option-adjusted spread, duration, and size biases significantly increase the predictive power of style factors. We propose a new simple approach for efficiently neutralizing the biases from multiple risk variables and demonstrate its superiority relative to stratified sampling and optimization as alternative control methods. We also measure the added value from diversifying the number of factors in each style. Finally, we show that the results are robust in relation to transaction costs and can be used to design strategies that aim at outperforming traditional benchmark indexes. TOPICS: Analysis of individual factors/risk premia, factor-based models, style investing Key Findings • Factors from value, quality, low-risk, and momentum styles play an important role in explaining the cross-section of corporate bond expected returns for the US and Euro Investment Grade and US BB-B Nonfinancial High Yield universes. • The forecasting efficacy of style factors increases significantly if biases such as sectors, option-adjusted spread, duration, and size in the factor data are neutralized. Diversifying the number of factors in each style also significantly improves the forecasting efficacy. • We propose a new simple approach for increasing the forecasting efficacy of style factors by efficiently neutralizing the biases from multiple risk variables. We demonstrate the superiority of this approach over stratified sampling and optimization.
企业债券市场的要素投资:通过多元化和净化来增强效力!
我们表明,价值、质量、低风险和动量风格的因素在解释美国和欧洲投资级和美国BB-B非金融高收益领域公司债券预期回报的横截面方面发挥了重要作用。我们通过中和因素中存在的一些风险偏差来证明净化因素数据的重要性:控制行业,期权调整的价差,持续时间和规模偏差显着增加了风格因素的预测能力。我们提出了一种新的简单方法来有效地中和来自多个风险变量的偏差,并证明了它相对于分层抽样和优化作为替代控制方法的优越性。我们还测量了每种风格中多样化因素数量所带来的附加值。最后,我们证明了结果在交易成本方面是稳健的,并且可以用于设计旨在优于传统基准指数的策略。•来自价值、质量、低风险和动量风格的因素在解释美国和欧洲投资级和美国BB-B非金融高收益领域公司债券预期回报的横截面方面发挥了重要作用。•如果消除因素数据中的行业、期权调整价差、持续时间和规模等偏差,风格因素的预测效果将显著提高。使每种风格的因子数量多样化也显著提高了预测效果。•我们提出了一种新的简单方法,通过有效地中和来自多个风险变量的偏差来提高风格因素的预测效果。我们证明了这种方法优于分层抽样和优化。
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来源期刊
Journal of Fixed Income
Journal of Fixed Income Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
1.10
自引率
0.00%
发文量
23
期刊介绍: The Journal of Fixed Income (JFI) provides sophisticated analytical research and case studies on bond instruments of all types – investment grade, high-yield, municipals, ABSs and MBSs, and structured products like CDOs and credit derivatives. Industry experts offer detailed models and analysis on fixed income structuring, performance tracking, and risk management. JFI keeps you on the front line of fixed income practices by: •Staying current on the cutting edge of fixed income markets •Managing your bond portfolios more efficiently •Evaluating interest rate strategies and manage interest rate risk •Gaining insights into the risk profile of structured products.
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